The present disclosure relates generally to systems, methods and devices for closed loop deep brain stimulation. Briefly, a model of the brain is formed in software and is continuously updated by neural signals. The model is used to determine stimulation signals sent to the human brain, and the resulting neural signals are used to provide feedback to the software model of the brain.
Millions of people suffer from neurological disorders such as Parkinson's Disease (PD), epilepsy, essential tremor, dystonia, depression, and obsessive-compulsive disorder. One treatment for these conditions is deep brain stimulation (DBS), wherein a brain pacemaker is implanted into the brain of a patient. The brain pacemaker sends electrical impulses to specific parts of the brain to treat the neurological disorder. DBS can be very effective at managing the symptoms of Parkinson's, which consequently greatly improves the patient's quality of life. DBS may be helpful for certain cases of epilepsy by reducing the frequency and severity of epileptic seizures.
Some commercial brain pacemaker devices have the capability to both electrically stimulate the brain and also sense electrical signals from the brain. However, the devices currently lack working closed loop feedback. Because the devices lack working closed loop feedback, the electrical stimulation delivered by the device must be manually adjusted in repeated office visits. An example of such a device is the Medtronic Brain Radio. It would be desirable to provide fully automatic closed-loop systems that provide feedback (use the output signal as an input) so that effective deep brain stimulation is provided.